Impacts of climate extremes on variations in evergreen forest ecosystem carbon–water fluxes across Southern China

Abstract

Climate extremes exert detrimental influences on the water retention capacity and carbon sequestration functions of forest ecosystems. However, the response mechanisms of carbon–water cycles and their coupling relationships to climate extremes remain unclear. To address these issues, we investigated in an evergreen forest ecosystem located in Southern China, with comprehensive datasets and machine learning (ML) algorithms, where water–use efficiency (WUE) is defined as the ratio of gross primary production (GPP) to evapotranspiration (ET). The spatial–temporal distribution characteristics of GPP, ET, and WUE, as well as their responses to observed extreme weather events (torrential rains, drought, heat wave and cold wave) and climate extreme indices (CEIs) during 1979–2017 were investigated. We evaluated the accuracy of 8 types of ML algorithms in modelling observed GPP and ET, and the extreme gradient boosting model showed the best performance (GPP: R² = 0.91–0.98, ET: R² = 0.84–0.98). Regionally averaged annual values indicated significant increasing (p < 0.01) trends for GPP (3.28 gC m⁻² a⁻²), ET (0.62 mm a⁻²), and WUE (0.0023 gC m⁻² mm⁻¹ a⁻¹), with mean annual values exhibiting a gradient increase from the northwest to southeast. Across the 21 CEIs, the precipitation–related indices showed positive correlations with GPP and ET, and the warm (cold)–related temperature indices showed positive (negative) correlations with these fluxes. These fluxes were more sensitive to torrential rains and cold wave, during which the response of ET was more immediate, while the negative impact of cold wave on GPP gradually intensified over time. As a result, WUE initially remained stable but then declined sharply during cold period. Overall, the carbon–water fluxes for evergreen forests on Southern China were most likely to exhibit high risk during cold events. Our findings provide valuable references for the response of evergreen forests to climate extremes.